by diavelguru
4 subcomments
- This is a real thing. I spent all of January doing Greenfield development using Claude (I finished the requirements) and all I can say is thank goodness I had the Max 5x plan and not the 20x as I got breaks once the tokens were used up till the next cycle. I was forced to get up and do something else. That something else was biking, rowing, walking. My productivity had never been higher but at what cost? My health no thanks. So I'm glad I'm using the time till token reset for my health. I time it perfectly. I do a walk, row, bike for 1 hour then as I arrive back the tokens are reset. I get like 3 hours nonstop use per token batch with the 5x plan. I've been thinking about going 20x but am scared...
- When people talk about AI increasing developer productivity, they usually focus on the coding part.
In my experience, the bigger change happens after the code is written.
When you move from writing code to supervising agents, your output increases — but your cognitive load increases too.
Instead of writing every line yourself, you're now monitoring systems:
Did the agent go off-script?
Did it retry 50 times while I was asleep?
What did that run actually cost?
The strange part is that the mental burden doesn't disappear just because the agent is autonomous.
In some ways it gets worse, because failures become harder to notice early and harder to contain once they start.
It starts to feel less like programming and more like running operations for a team of extremely fast, extremely literal junior developers.
Curious if others are seeing the same shift.
by furyofantares
4 subcomments
- > Software engineering was supposed to be artificial intelligence’s easiest win.
At what point in time? Did anyone foresee coding being one of the best and soonest applications of this stuff?
- Selection bias? The early adopters that are motivated to adopt tools to deliver more, typically also were working more to start with and may have already been struggling with their rate of output?
by kazinator
1 subcomments
- Prior to the rise of LLM coding, developers had to, from time to time, spent time deep diving through large amounts of code they didn't write. Hundreds of thousands of lines or even millions. This might happens when starting a new job, or changing projects, or when tasked with evaluating some third party tech or integrating it, or taking over something that was previously owned by another developer.
During such phases of work, it's not unusual to put in some long hours in order to get up to speed.
With LLMs, it is possible to perpetually experience hundreds of thousands of lines of third party code, on about a weekly basis.
But this is not the same. The code is not known by anyone, anywhere else. It exists nowhere else, and so has no track record of deployment. No documentation, nothing. It's not something where you can concentrate on making a small modification, while trusting the rest of it to be working.
- I use it every day and I'm taking off weekends for the first time in a decade. It's done wonders for my mental health. I think teams should pay more attention to the value of pumping the brakes vs. incessant redlining. We may actually be able to have a healthy relationship with AI then.
by butILoveLife
1 subcomments
- We've become cashiers.
My 6 year old is doing my job.
The best I can hope for is that HN article that said the word "Context".
I know the magic words "Make me a single page html js web app"... or "Install Virtual Box with Fedora Cinnamon using CLI"....
I'm 8x more productive than I was in 2022... And I jokingly say "I'm probably not going to have a job in 1 or 2 years"...
We are going to create incredible value to humanity. 8x rate. I don't know what our hourly will be.
- Personally, I make a lot more "out of hour" commits than I used to because I'll batch up low priority tasks throughout the day and let the computer chug on them at night when I'm elsewhere. Commits are coming in at all hours, but I'm not actually looking at them until the next morning.
- I feel totally the opposite. I feel like I'm better able to have more work-life balance. Our predictions are more accurate. I'm enjoying working on actual problems rather than boilerplate. These tools are amazing
- two unthought out thoughts:
1. llms allow devs to be more productive, so more free time is seen as opportunity for more work. ppl overshoot and just work more
2. generalized tooling makes devs seem more replaceable putting downward pressure on job security (ie work harder or we’ll get someone who will, oh and for less money)
3. llms allow for more “multitasking” (debatable) via many running background tasks, so more opportunities to “just finish one more thing”
by SoftTalker
0 subcomment
- No silver bullet. We've known this since at least the 1980s. The fact that the authors of the code might not be human doesn't change this.
- thouroughly reviewing and especially testing is faster than skipping manual review and tests
- I can't deny that this might be a trend in practice, but at companies with reasonably self-aware practices, it isn't, or doesn't need to be.
There's this weird thing that happens with new tools where people seem to surrender their autonomy to them, e.g. "welp, I just get pings from [Slack|my phone|etc] all the time, nothing I can do than just be interrupted constantly." More recently, it's "this failed because Claude chose..." No, Claude didn't choose, the person who submitted the PR chose to accept it.
It's possible to use tools responsibly and effectively. It's also possible to encourage and mentor employees to do that. The idea that a dev has to be effectively on call because they're pushing AI slop is just wrong on so many levels.
by decker_dev
2 subcomments
- [dead]
by aplomb1026
0 subcomment
- [dead]
by shablulman
0 subcomment
- [dead]
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